Maral Saadati

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The composition of tumor-targeted T cell infiltrates is a major prognostic factor in colorectal cancer (CRC) outcome; however, the functional role of these populations in prolonging patient survival remains unclear. Here, we evaluated 190 patients with CRC for the presence of functionally active tumor-infiltrating lymphocytes (TILs), the tumor specificity(More)
Neuroblastoma is a malignant paediatric tumour of the sympathetic nervous system. Roughly half of these tumours regress spontaneously or are cured by limited therapy. By contrast, high-risk neuroblastomas have an unfavourable clinical course despite intensive multimodal treatment, and their molecular basis has remained largely elusive. Here we have(More)
The broad clinical spectrum of neuroblastoma ranges from spontaneous regression to rapid progression despite intensive multimodal therapy. This diversity is not fully explained by known genetic aberrations, suggesting the possibility of epigenetic involvement in pathogenesis. In pursuit of this hypothesis, we took an integrative approach to analyze the(More)
With the fast growing field of epigenetics comes the need to better understand the intricacies of DNA methylation data analysis. High-throughput profiling using techniques, such as Illumina's BeadArray assay, enable the quantitative assessment of methylation. Challenges arise from the fact that resulting methylation levels (so-called beta values) are(More)
Uncontrolled cell cycle entry, resulting from deregulated CDK-RB1-E2F pathway activity, is a crucial determinant of neuroblastoma cell malignancy. Here we identify neuroblastoma-suppressive functions of the p19-INK4d CDK inhibitor and uncover mechanisms of its repression in high-risk neuroblastomas. Reduced p19-INK4d expression was associated with poor(More)
One important task in translational cancer research is the search for new prognostic biomarkers to improve survival prognosis for patients. The use of high-throughput technologies allows simultaneous measurement of genome-wide gene expression or other genomic data for all patients in a clinical trial. Penalized likelihood methods such as lasso regression(More)
We consider modeling competing risks data in high dimensions using a penalized cause-specific hazards (CSHs) approach. CSHs have conceptual advantages that are useful for analyzing molecular data. First, working on hazards level can further understanding of the underlying biological mechanisms that drive transition hazards. Second, CSH models can be used to(More)
Skeletal involvement (SI) is observed at low prevalence in patients with diffuse large B-cell lymphoma (DLBCL). Due to the rareness of this particular condition, prospective trials for these patients are scarce. We analyzed clinical characteristics and outcome of 75 patients with DLBCL and SI in order to identify factors with prognostic impact towards(More)
MOTIVATION Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size settings, which are typical for molecular data. Assuming that the underlying signal is(More)
Motivation: Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size settings, which are typical for molecular data. Assuming that the underlying signal(More)
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